Turn-Level Keyword Transition.
Given \(Q_N\) , \(\mathcal {H}_N = \lbrace  Q_{<N}, A_{<N} \rbrace \) , this module predicts a set of candidate keywords of the next response \(A_N\)  which are appropriate in the conversational context. Since keyword prediction is agnostic to the end target, any open-domain chat data where each dialog turn is labeled by keyword(s) can be used to train the keyword predictor. The predictor can be implemented as a statistical model based on pairwise mutual information, or neural matching models [1]}.
